The invention generally relates to techniques for monitoring the effectiveness of medical therapies and dosage formulations, and in particular to techniques for monitoring therapy effectiveness using viral load measurements.
It is often desirable to determine the effectiveness of therapies, such as those directed against viral infections, including therapies involving individual drugs, combinations of drugs, or other related therapies. One conventional technique for monitoring the effectiveness of a viral infection therapy is to measure and track a viral load associated with the viral infection, wherein the viral load is a measurement of a number of copies of the virus within a given quantity of blood, such per milliliter of blood. The therapy is deemed effective if the viral load is decreased as a result of the therapy. A determination of whether any particular therapy is effective is helpful in determining the appropriate therapy for a particular patient and also for determining whether a particular therapy is effective for an entire class of patients. The latter is typically necessary in order to obtain FDA approval of any new drug or medical device therapy. Viral load monitoring is also useful for research purposes such as for assessing the effectiveness of new antiviral compounds determine, for example, whether it is useful to continue developing particular antiviral compounds or to attempt to gain FDA market approval.
A test to determine the viral load can be done with blood drawn from T-cells or from other standard sources. The viral load is typically reported either as an absolute number, i.e., the number of virus particles per milliliter of blood or on a logarithmic scale. Likewise, decreases in viral load are reported in absolute numbers, logarithmic scales, or as percentages.
It should be noted though that a viral load captures only a fraction of the total virus in the body of the patient, i.e., it tracks only the quantity of circulating virus. However, viral load is an important clinical marker because the quantity of circulating virus is the most important factor in determining disease outcome, as changes in the viral load occur prior to changes in other detectable factors, such as CD4 levels. Indeed, a measurement of the viral load is rapidly becoming the acceptable method for predicting clinical progression of certain diseases such as HIV.
Insofar as HIV is concerned, HIV-progression studies have indicated a significant correlation between the risk of acquiring AIDS and an initial HIV baseline viral load level. In addition to predicting the risk of disease progression, viral load testing is useful in predicting the risk of transmission. In this regard, infected individuals with higher viral load are more likely to transmit the virus than others.
Currently, there are several different systems for monitoring viral load including quantitive polymerase chain reaction (PCR) and nucleic acid hybridization. Herein, the term viral load refers to any virological measurement using RNA, DNA, or p24 antigen in plasma. Note that viral RNA is a more sensitive marker than p24 antigen. p24 antigen has been shown to be detectable in less than 50% asymptomatic individuals. Moreover, levels of viral RNA rise and fall more rapidly than levels of CD4+ lymphocytes. Hence, changes in infection can be detected more quickly using viral load studies based upon viral RNA than using CD4 studies. Moreover, viral load values have to date proven to be an earlier and better predictor of long term patient outcome than CD4-cell counts. Thus, viral load determinations are rapidly becoming an important decision aid for anti-retro viral therapy and disease management. Viral load studies, however, have not yet completely replaced CD+ analysis in part because viral load only monitors the progress of the virus during infection whereas CD4+ analysis monitors the immune system directly. Nevertheless, even where CD4+ analysis is effective, viral load measurements can supplement information provided by the CD4 counts. For example, an individual undergoing long term treatment may appear stable based upon the observation of clinical parameters and CD4 counts. However, the viral load of the patient may nevertheless be increasing. Hence, a measurement of the viral load can potentially assist a physician in determining whether to change therapy despite the appearance of long term stability based upon CD4 counts.
Thus, viral load measurements are very useful. However, there remains considerable room for improvement. One problem with current viral load measurements is that the threshold level for detection, i.e., the nadir of detection, is about 400-500 copies per milliliter. Hence, currently, if the viral load is below 400-500 copies per milliliter, the virus is undetectable. The virus may nevertheless remain within the body. Indeed, considerable quantities of the virus may remain within the lymph system. Accordingly, it would be desirable to provide an improved method for measuring viral load which permits viral load levels of less than 400-500 copies per milliliter to be reliably detected.
Another problem with current viral load measurement techniques is that the techniques are typically only effective for detecting exponential changes in viral loads. In other words, current techniques will only reliably detect circumstances wherein the viral load increases or decreases by an order of magnitude, such by a factor of 10. In other cases, viral load measurements only detect a difference between undetectable levels of the virus and detectable levels of the virus. As can be appreciated, it would be highly desirable to provide an improved method for tracking changes in viral load which does not require an exponential change in the viral load for detection or which does not require a change from an undetectable level to a detectable level. Indeed, with current techniques, an exponential or sub-exponential change in the viral load results only in a linear change in the parameters used to measure the viral load. It would instead be highly desirable to provide a method for monitoring the viral load which converts a linear change in the viral load into an exponential change within the parameters being measured to thereby permit very slight variations in viral load to be reliably detected. In other words, current viral load detection techniques are useful only as a qualitative estimator, rather than as a quantative estimator.
One reason that current viral load measurements do not reliably track small scale fluctuations in the actual number of viruses is that a significant uncertainty in the measurements often occurs. As a result, individual viral load measurements have little statistical significance and a relatively large number of measurements must be made before any statistically significant conclusions can be drawn. As can be appreciated it would be desirable to provide a viral load detection technique which can reliably measure the viral load such that the statistical error associated with a single viral load measurement is relatively low to permit individual viral load measurements to be more effectively exploited.
Moreover, because individual viral load measurements are not particularly significant when using current methods, treatment decisions for individual patients based upon the viral load measurements must be based only upon long term changes or trends in the viral load resulting in a delay in any decision to change therapy. It would be highly desirable to provide an improved method for measuring and tracking viral load such that treatment decisions can be made much more quickly based upon short term trends of measured viral load.
As noted above, the current nadir of viral load detectability is at 400-500 copies of the virus per milliliter. Anything below that level is deemed to be undetectable. Currently the most successful and potent multi-drug therapies are able to suppress viral load below that level of detection in about 80-90 percent of patients. Thereafter, viral load is no longer an effective indicator of therapy. By providing a viral load monitoring technique which reduces the nadir of detectability significantly, the relative effectiveness of different multi-drug therapies can be more effectively compared. Indeed, new FDA guidelines for providing accelerated approval of a new drug containing regimen requires that the regimen suppress the viral load below the current nadir of detection in about 80 to 85 percent of cases. If the new regimen suppresses the viral load to undetectable levels in less than 80 to 85 percent of the cases, the new drug will gain accelerated approval only if it has other redeeming qualities such as a preferable dosing regimen (such as only once or twice per day), a favorable side effect profile, or a favorable resistance or cross-resistance profile. Thus, the ability of a regimen to suppress the viral load below the level of detection is an important factor in FDA approval. However, because the level of detectability remains relatively high, full approval is currently not granted by the FDA solely based upon the ability of the regimen to suppress the viral load below the minimum level of detection. Rather, for full approval, the FDA may require a further demonstration of the durability of the regimen, i.e., a demonstration that the drug regimen suppresses the viral load below the level of detectability and keeps it below the level of detectability for some period of time.
As can be appreciated, if a new viral load measurement and tracking technique were developed which could reliably detect viral load at levels much lower than the current nadir of detectability, the FDA may be able, using the new technique, to much more precisely determine the effectiveness of a drug regimen for the purposes of granting approval such that a demonstration of the redeeming evalities will no longer be necessary.
For all of these reasons, it would be highly desirable to provide an improved technique for measuring and tracking viral load capable of providing much more precise and reliable estimates of the viral load and in particular capable of reducing the nadir of detectability significantly. The present invention is directed to this end.
In accordance with a first aspect of the invention, a method is provided for determining the effectiveness of a therapy, such as an anti-viral therapy, by analyzing biochip output patterns generated from biological samples taken at different sampling times from a patient undergoing the therapy. In accordance with the method, a viral diffusion curve associated with a therapy of interest is generated and each of the output patterns representative of hybridization activity is then mapped to coordinates on the viral diffusion curve using fractal filtering. A degree of convergence between the mapped coordinates on the viral diffusion curve is determined. Then, a determination is made as to whether the therapy of interest has been effective based upon the degree of convergence.
In an exemplary embodiment, the viral diffusion curve is spatially parameterized such that samples map to coordinates near the curve maxima, if the viral load is increasing (i.e., therapy or dosage is ineffective). In this manner, any correlation between rate and extent of convergence across different patient samples is exploited to provide a quantitative and qualitative estimate of therapy effectiveness.
Also in the exemplary embodiment, the biological sample is a DNA sample. The output pattern of the biochip is quantized as a dot spectrogram. The viral diffusion curve is generated by inputting parameters representative of viral load studies for the therapy of interest, generating a preliminary viral diffusion curve based upon the viral load studies; and then calibrating a degree of directional causality in the preliminary viral diffusion curve to yield the viral diffusion curve. The parameters representative of the viral load studies include one or more of baseline viral load (BVL) set point measurements at which detection is achieved, BVL at which therapy is recommended and viral load markers at which dosage therapy is recommended. The step of generating the preliminary viral diffusion curve is performed by selecting a canonical equation representative of the viral diffusion curve, determining expectation and mean response parameters for use in parameterizing the equation selected to represent the viral diffusion curve and parameterizing the equation selected to represent the viral diffusion curve to yield the preliminary viral diffusion curve.
Also, in the exemplary embodiment, each dot spectrogram is mapped to the viral diffusion curve using fractal filtering by generating a partitioned iterated fractal system IFS model representative of the dot spectrogram, determining affine parameters for IFS model, and then mapping the dot spectrogram onto the viral diffusion curve using the IFS. Before the dot spectrograms is mapped to the viral diffusion curve, the dot spectrograms are interferometrically enhanced. After the mapping, any uncertainty in the mapped coordinates is compensated for using non-linear information filtering.
In accordance with a second aspect of the invention, a method is provided for determining the viral load within a biological sample by analyzing an output pattern of a biochip to which the sample is applied. In accordance with the method, a viral diffusion curve associated with a therapy of interest is generated and then calibrated using at least two viral load measurements. Then the output pattern for the sample is mapped to coordinates on the calibrated viral diffusion curve using fractal filtering. The viral load is determined from the calibrated viral diffusion curve by interpreting the coordinates of the viral diffusion curve.
Apparatus embodiments are also provided. By exploiting aspects of the invention, disease management decisions related to disease progression, therapy and dosage effectiveness may be made by tracking the coordinates on the viral diffusion curve as successive DNA-/RNA-based microarray samples are collected and analyzed.